vugia truong's Projects
Use a depth camera on Baxter's wrist to scan an object's 3D point cloud
6D - Pose Annotation Tool (6D-PAT) - is a tool that allows the user to load a set of images and also a set of 3D models and annotate where in the 2D image the 3D object ist placed.
This package integrates a library for scene recognition based on implicit shape models (ISM) to the ros environment
Image augmentation library in Python for machine learning.
ROS node implementation of a simple Next Best View algorithm based on voxel grid, view sphere sampling, ray tracing and unknown voxel count.
Some examples for the use of boost::python
example using boost_python with anaconda/miniconda
Example using celery
Chainer implementation of Pose Proposal Networks
CheatSheetのまとめ場所
Translation of VIP cheatsheets for Machine Learning and Deep Learning
ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
:pencil2: Web-based image segmentation tool for object detection and localization
A Code-First Introduction to NLP course
Official implementation of Character Region Awareness for Text Detection (CRAFT)
Convolutional recurrent network in pytorch
Python implementation of "Single Image Haze Removal Using Dark Channel Prior"
Put masked object onto background images randomly to generate images. Train Yolo3.
Image Deblurring using Generative Adversarial Networks
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
Text recognition (optical character recognition) with deep learning methods.
Playing with insightface
(1) 3D scan object by Baxter. (2) Label objects automatically by depth camera and (3) train Yolo. (4) [TODO; NOT DONE YET!!!] Finally, detect object and fit 3D model to know the 6D pose.
Learning pytorch
This repository contains code for training and evaluating various Deep Metric Learning (DML) algorithms on the CUB200-2011, Cars196 and SOP datasets.
Object 6DoF Pose Estimation for Assembly Robots Trained on Synthetic Data - ROS Kinetic/Melodic Using Intel® RealSense D435